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Let’s Listen to the Data: Sonification for Learning Analytics

Part of the Communications in Computer and Information Science book series (CCIS,volume 1112)


This paper falls in the field of playing analytics. It deals with an empirical work dedicated to explore the potential of data sonification (i.e. the conversion of data into sound that reflects their objective properties or relations). Data sonification is proposed as an alternative to data visualization. We applied data sonification for the analysis of gameplays and players’ strategies during a session dedicated to game-based learning. The data of our study (digital traces) was collected from 200 pre-service teachers who played Tamagocours, an online collaborative multiplayer game dedicated to learn the rules (i.e. copyright) that comply with the policies for the use of digital resources in an educational context. For one typical individual (parangon) for each of the 5 categories of players, the collected digital traces were converted into an audio format so that the actions that they performed become listenable. A specific software, SOnification of DAta for Learning Analytics (SODA4LA), was developed for this purpose. The first results show that different features of the data can be recognized from data listening. These results also enable for the identification of different parameters that should be taken into account for the sonification of diachronic data. We consider that this study open new perspectives for playing analytics. Thus we advocate for new research aiming at exploring the potential of data sonification for the analysis of complex and diachronic datasets in the field of educational sciences.


  • Sonification
  • Playing analytics
  • Data visualisation
  • Game-based learning
  • Learning Analytics

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  • DOI: 10.1007/978-3-030-33232-7_16
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Correspondence to Eric Sanchez or Théophile Sanchez .

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Sanchez, E., Sanchez, T. (2019). Let’s Listen to the Data: Sonification for Learning Analytics. In: Eagan, B., Misfeldt, M., Siebert-Evenstone, A. (eds) Advances in Quantitative Ethnography. ICQE 2019. Communications in Computer and Information Science, vol 1112. Springer, Cham.

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  • Print ISBN: 978-3-030-33231-0

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